No abstract

Satisfying a context consumer’s quality of context (QoC) requirements is of utmost importance to context management platforms (CMPs)in order to have credibility. QoC indicates the contextual information’s quality metrics (e.g., accuracy, timeliness, completeness). The outcomes of these metrics depend on the functional and quality characteristics associated with all actors (context consumers (or) context-aware applications, CMPs, and context providers (or) IoT-data providers) in context-aware ecosystems. This survey identifies and studies such characteristics and highlights the limitations in actors’ current functionalities and QoC modelling approaches to obtain adequate QoC and improve context consumers’ quality of experience (QoE). We propose an abstract system based on deductions from this study; this system addresses the functional limitations in existing QoC modelling approaches. Moreover, we have also highlighted those QoC metrics affected by quality of service (QoS) metrics in CMPs. These recommendations provide CMP developers with a reference framework they could incorporate and a list of QoS metrics that they need in order to maintain an adequate QoC.

Despite the potential benefits of the context-driven intelligence delivered by Context Management Platforms (CMP), the lack of efficient and effective metrics for measuring Quality and Cost of Context (QoC and CoC) hinders them from uptake and commercialisation. Furthermore, the CMPs might have limited abilities to incorporate efficient QoC drivers and a suboptimal selection of QoC-aware context providers. This paper proposes QoC and CoC metrics and introduces a conceptual architecture to achieve the QoC and CoC awareness in CMPs, aiming to improve their efficiency and consumer experience. RÉSUMÉ. En dépit des bénéfices potentiels d'une intelligence guidée par le context que délivrent les plates-formes de management des contexts (CMP), le manqué de métriques fonctionnelles et efficaces pour mesurer la qualité et le coût du contexte (QoC and CoC) limitent l'adoption et la commercialisation de ces métriques. En outre, ces CMPs peuvent avoir des capacités limitées pour incorporer une QoC efficace et une sélection sous-optimale des fournisseurs de contextes sensibles à la QoC. Ce papier pose des métriques qoC et CoC, introduit une architecture conceptuelle pour réaliser la sensibilité à QoC et CoC dans les CMPs, visant à améliorer leur efficacité et l'expérience du consommateur de contextes.

No abstract

No abstract